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Privacy implications of voice and speech analysis - information disclosure by inference

: Kröger, Jacob Leon; Lutz, Otto Hans-Martin; Müller, Florian; Raschke, P.

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Friedewald, Michael (Ed.); Önen, Melek (Ed.); Lievens, Eva (Ed.); Krenn, Stephan (Ed.); Fricker, Samuel (Ed.) ; International Federation for Information Processing -IFIP-:
Privacy and identity management. Data for better living: AI and privacy : 14th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2. International Summer School, Windisch, Switzerland, August 19-23, 2019, Revised Selected Papers
Cham: Springer International Publishing, 2020 (IFIP advances in information and communication technology 576)
ISBN: 978-3-030-42503-6
ISBN: 978-3-030-42504-3
DOI: 10.1007/978-3-030-42504-3
Summer School on Privacy and Identity Management "Data for Better Living - Artificial Intelligence and Privacy" <14, 2019, Brugg/Windisch>
Conference Paper, Electronic Publication
Fraunhofer FOKUS ()

Internet-connected devices, such as smartphones, smartwatches, and laptops, have become ubiquitous in modern life, reaching ever deeper into our private spheres. Among the sensors most commonly found in such devices are microphones. While various privacy concerns related to microphone-equipped devices have been raised and thoroughly discussed, the threat of unexpected inferences from audio data remains largely overlooked. Drawing from literature of diverse disciplines, this paper presents an overview of sensitive pieces of information that can, with the help of advanced data analysis methods, be derived from human speech and other acoustic elements in recorded audio. In addition to the linguistic content of speech, a speaker's voice characteristics and manner of expression may implicitly contain a rich array of personal information, including cues to a speaker's biometric identity, personality, physical traits, geographical origin, emotions, level of intoxication and sleepiness, age, gender, and health condition. Even a person's socioeconomic status can be reflected in certain speech patterns. The findings compiled in this paper demonstrate that recent advances in voice and speech processing induce a new generation of privacy threats.